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SAS® Model Manager

Create, manage and deploy lifecycle analytics

SAS Model Manager streamlines the tedious and often error-prone steps of creating, managing and deploying analytical models, and continually verifies their accuracy and usefulness. Because analytics play an important role in business processes, it is critical that organizations reduce the likelihood of erroneous model output or incorrect interpretation of model results.

Benefits

  • Manage and deploy models more quickly.
  • Track and monitor model performance.
  • Comply with regulatory requirements.
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Features

  • Central, secure repository for managing analytical models.
  • Prebuilt templates for model registration.
  • Model repository query by attributes.
  • Secure model storage and access administration.
  • Validation of scoring logic.
  • Model performance and comparison reports.
  • Overall lifecycle management of analytical models.
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This application really works for us because our extraction logic is written once and stored centrally. This facilitates the parallel extraction of data. SAS also takes care of the complex data extraction process, which is a benefit to the modeller.

— Carl Touchie,

Managing Director of Decision Support Services,

BMO Bank of Montreal

Screenshots

SAS Model Manager's easy-to-use GUI.

SAS Model Manager
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How SAS Is Different

  • SAS Model Manager enables organizations to effectively create, manage and deploy statistical, predictive, classification and analytical scoring models in an enterprise computing environment.
  • It provides a patented, secure, centralized repository for storing and organizing models backed by extensive documentation templates for each model.
  • Accountability metrics and validation of analytical steps, from the time of creation through deployment into real-time or batch scoring systems, continues until the time a model must be retired.
 

Ready to learn more?

Call us at 01628 486 933 (UK) or request more information.

 

Questions?

 

White Paper

Best Practices for Managing Predictive Models in a Production Environment